Attitude measurement using a single GPS receiver with two closely-spaced antennas

ABSTRACT

A system determines three-dimensional attitude of a moving platform using signals from two closely spaced Global Positioning System (GPS) antennas. The system includes three rate gyroscopes and three accelerometers rigidly mounted in a fixed relationship to the platform to aid in determining the attitude. The system applies signals from a first of the two GPS antennas to sufficient channels of a GPS receiver to support navigation. The system applies signals from a second of the two GPS antennas to the remaining receive channels, which are configured to support interferometry. The system optimally selects the navigation and interferometry channels to provide an interferometric heading solution. The system resolves the ambiguity normally associated with the interferometric heading solution by having the closely spaced GPS antennas and using interferometry to refine a coarse heading estimate from a GPS plus Inertial Measurement Unit (IMU) transfer alignment solution. The system achieves close sub-meter spacing of the two GPS antennas by merging many temporal interferometric measurements that result from an attitude memory provided by the IMU time-history solution.

RELATED APPLICATION(S)

[0001] This application claims the benefit of U.S. ProvisionalApplication No. 60/272,170, filed on Feb. 28, 2001; the entire teachingsof which are incorporated herein by reference.

GOVERNMENT SUPPORT

[0002] The invention was supported, in whole or in part, by contractsDAAB07-00-C-J603 and DAAB07-01-C-J403 from US Army CommunicationsElectronics Command. The Government has certain rights in the invention.

BACKGROUND OF THE INVENTION

[0003] The present invention relates to moving platforms, specifically,to a system for determining the geodetic attitude of an arbitrarilymoving platform. Moving platforms include vehicles, such as aircraft,ground vehicles, boats or spacecraft or equipment mounted to vehiclesthat can be reoriented relative to the vehicle body. The platforms maybe traveling at fast or slow speeds, may be maneuvering ornon-maneuvering, and may be occasionally stationary relative to geodeticspace. These platforms require knowledge of their geodetic attitude inorder, for example, (i) to support safety or stability control systems,(ii) to point an antenna or sensor boresight at a geodetically knowntarget, (iii) to control their geodetic position or attitude movement,or (iv) to register the information sensed along the boresight onto amap projection with geodetic coordinates. The sensor or antennaboresight is the centerline of some signal collection or signaltransmission aperture. Earth-rate sensing through gyrocompassing, GPSinterferometry, and transfer alignment (TA) are possible implementationapproaches for precision geodetic orientation measurement systems forarbitrary moving platforms. Each technique is in widespread use, buteach technique alone has significant limitations for precision pointing.

[0004] Earth rate sensing requires the use of a gyroscope with accuracymuch better than the earth's 15-deg/hr-rotation rate. The gyroscopesused for conventional gyrocompass systems have drift specifications ofless than 0.1 deg/hr. Modern military gyroscopes, currently used onmissiles, can achieve a 1 deg/hr accuracy with prices of about $5000 inlarge quantities. For a 1-deg/hr tactical weapon grade gyroscope, thenorth seeking accuracy is about 4 deg and is not sufficiently accuratefor broadband pointing.

[0005] GPS interferometry measures GPS carrier phase to GPS satellitesfrom multiple spaced antennas. Carrier phase differencing removes allcommon mode ionospheric corruption from the differenced signals. Theremaining phase difference can be used to infer range to GPS satellitesto millimeter (mm) accuracy. The measurement is corrupted bycable-induced phase differences, on-vehicle multipath, and a whole-cycleGPS wavelength ambiguity that is 19 cm for commercial GPS. A method notbased on interferometry is often used to get close to the correctattitude and reduce whole-cycle ambiguity. Commercial motioncharacterization systems that use GPS interferometry are available, butimpose installation difficulties by requiring multiple antennasdispersed over several square meters. Also, the lack of wide-bandwidthattitude memory prevents any accuracy enhancement through data averagingunless the system is perfectly stationary.

[0006] Transfer alignment is the most widely used precision orientationmeasurement method for military applications. Transfer alignmentsynergistically combines an Inertial Navigation System (INS) withsingle-antenna GPS system to estimate position and attitude. The INS,traditionally used only in military applications and high-end aircraft,has an internal instrument suite that provides measurement of three axesof acceleration and three axes of rotation rate. Mathematicalmanipulation of the acceleration and rotation rate measurements providesthe position, velocity, and attitude of the platform at a highbandwidth. However, the navigation solution will drift unless someexternal corrections are incorporated. For low cost inertial components,the drift will occur rapidly. GPS external measurement is most oftenused for the INS corrections. For GPS transfer alignment, INS-derivedvelocity and GPS-derived velocity are differenced, and the time-historyof the differences is then used to infer errors in assumed geodeticalignment of the INS axes. The need to maintain persistent changingvelocity to enable attitude measurement and the traditional high cost ofthe INS make TA unsuitable for most commercial applications. TA uses amathematics model where attitude errors propagate into the IMU-derivedplatform position and velocity in geodetic coordinates. By independentlymeasuring the geodetic position and velocity with the navigation GPSsolution, the attitude errors are observed and corrected. However, theattitude errors are observable through the velocity, such that a changein attitude produces a change in geodetic velocity. The presence of aspecific force acting on the platform must be present to impart attitudeobservability. A specific force is almost always present in the verticaldirection since a force must be imposed to maintain the platform fromfalling towards the center of the earth. Thus, attitude orthogonal tothe vertical direction, the platform roll and pitch angles, are readilyobserved for any platform not in a free-fall condition. However, aplatform at a constant velocity in the horizontal plane will have noobservability of attitude about the vertical direction, the platform yawangle. For successful transfer alignment, the horizontal plane motionmust be sensed by the GPS carrier phase measurements from the navigationGPS antenna. Because integrated carrier phase measurements are accurateto millimeter (mm) levels, even for a very low cost commercial receiver,only a slight platform motion is sufficient for some level of headingattitude measurement. Most moving platforms will have some motion fromexternal disturbances for attitude estimation to an accuracy of severaldegrees.

[0007] In addition to the techniques just described, the prior art alsoincludes patents teaching techniques to determine geodetic attitude frommoving vehicles. For example, U.S. Pat. No. 5,575,316 to Buchlerdescribes a generalized motion characterization system employingmultiple GPS antennas and receivers and an IMU device. Key to Buchler'spreferred embodiment of this device, and clearly stated throughout hissample embodiment and claims, is a requirement to overcome a largeuncertainty in the initial platform heading. This initial heading error,coupled with a 1 m GPS antenna spacing, causes the GPS interferometricrange-to-satellite ambiguities to produce ambiguous platform headingmeasurements. The large initial heading error of 10 deg stated byBuchler results from the use of gyrocompassing to ascertain initialplatform heading independent of GPS interferometry. Gyrocompassing, asis understood in the art, relates to sensing the rotation rate of the15-deg/hour-earth vector. The LN-200 IMU rate gyro employed in theBuchler invention has a gyro drift of 1 deg/hr that produces the 10 degheading error following a gyrocompass event. The majority of the Buchlerinvention relates to the refinement of the initial attitude uncertaintyto a level where no ambiguities are present in the final measurement.

[0008] The Buchler invention poses at least six considerations thatprevent low manufacturing cost, ease of installation, and operation witharbitrary platforms:

[0009] Two independent GPS receivers are required to determine doubledifference relationships used for the interferometric processing. Thismeans that two oscillators are used in the GPS RF front-enddownconversion process. The use of two oscillators causes addedmeasurement noise when carrier phase from the two channels aredifferenced. Also, the use of two independent GPS receivers increasesthe cost.

[0010] The use of a 1 deg/hr IMU, necessary for gyrocompassing attitudeinitialization, demands a relatively high-cost IMU unsuitable for mostcommercial applications.

[0011] The use of a gyrocompass stage to initiate the attitudemeasurement process is not suitable for arbitrary platform operations.Gyrocompassing restricts the platform motion and requires a significantperiod of initialization time.

[0012] The Buchler invention assumes the use of a barometric altimeterfor independent altitude measurement. Such a measurement is problematicfor all platforms because of the need to maintain a clean and preciselyoriented passage to ambient airflow.

[0013] The Buchler invention assumes that all GPS satellites visible onone antenna are also visible to the second antenna to arrive at thedouble differences used by a Kalman filter. This suggests a requirementfor use of either two standard GPS receivers, each tracking the same GPSsatellites, or specialized, more costly, receiver architecture withtwice the standard number of channels.

[0014] A problem is posed by the Buchler invention that relates toachievable accuracy of the attitude solution. The bulk of the embodimentrelates to the use of a double-difference phase function, which Buchlerclaims to treat as a scalar measurement to the Kalman filter. Doubledifferences result in M-1 scalar measurements for M GPS satellites beingtracked. However, the measurements are correlated because common GPSsatellite ranges are used in multiple measurements. Treating suchcorrelated measurements as uncorrelated scalar measurements by theKalman filter leads to a suboptimal filter, as is well known in the art.The embodiment mentions the use of a single-difference measurementformulation but does not describe how this mechanization will produceuncorrelated scalar measurements for the Kalman filter.

[0015] In another patent example, U.S. Pat. No. 5,617,317 to Ignagaidescribes a generalized motion characterization system employingmultiple GPS antennas and receivers and an IMU device. The Ignagaiinvention assumes the existence of a separate Inertial Sensor System onthe platform, distinct from the dual-antenna GPS system. Ignagai doesnot fully integrate the IMU rotation rate and acceleration measurementsinto the attitude measurement processing; instead, the Ignagai inventiontakes independently derived attitude information from the InertialSensor System and combines it with differential range informationdetermined from a two-antenna interferometric GPS system. Ignagai uses asimple three-state Kalman filter to smooth the angular misalignmentbetween the two independently derived heading angles. As in the Buchlerinvention, two independent GPS antenna/receivers are used coupled to adifferential range processor. The Inertial Sensor System is said to bean Attitude and Heading Reference System (AHRS), which is known with theart to be a self-contained navigation system employing a separateair-data system, as explained by Ignagai.

[0016] Ignagai describes three types of interferometric measurementprocessing: differential range, differential carrier phase, anddifferential integrated Doppler counts. Ignagai discusses antennaseparations of 10-20 m for the differential range measurement, 1-2 m forthe integrated Doppler count method, and “a possibility” of 3.75 inchesseparation for the differential carrier phase measurement. However, theembodiment develops only the formulations for the differential range andthe integrated Doppler count methods. Ignagai makes little mention ofthe interferometric heading ambiguity problem treated extensively byBuchler.

[0017] Ignagai discusses the heading initialization as using theaircraft cockpit magnetic compass for a stationary aircraft, or by usingthe aircraft track heading while the aircraft is taxiing on the ground.The aircraft track heading initialization process assumes that the IMUand antenna baseline are aligned with the taxi velocity so that theheading alignment is equal to the ground velocity vector as measuredfrom GPS. Ignagai notes that this is problematic for an in-airinitialization of the heading because the aircraft body attitude is notaligned with the velocity vector.

[0018] Seven considerations are posed by Ignagai that prevent achievinglow manufacturing cost, ease of installation, and ease of operation witharbitrary platforms:

[0019] Two independent GPS receivers are required to determine theinterferometric relationships used for the interferometric processing.This means that two oscillators are used in the GPS RF front-enddownconversion process that contributes to the phase measurement noise.Also, two GPS receivers increase the cost.

[0020] Ignagai assumes a separate and distinct Inertial Sensor System,such as an AHRS, that will be too costly for general commercialapplications.

[0021] The use of an aircraft track heading procedure for initializingthe heading measurement process is not generally suitable for platformswhere the IMU and GPS baseline are arbitrarily oriented with respect tothe platform velocity vector.

[0022] Ignagai assumes the use of an Air Data Sensor. Such a measurementsensor is problematic for all platforms because of the need to maintaina clean and precisely oriented passage to the ambient airflow.

[0023] Ignagai assumes that all GPS satellites visible to one antennaare also visible to the second antenna to arrive at the interferometricdifferences used by the Kalman filter. This suggests the requirement foreither using two standard GPS receivers that each tracks the same GPSsatellites or using a tailored receiver architecture with twice thestandard number of channels.

[0024] Ignagai uses a simple three-state Kalman filter for smoothing theinertial sensor and GPS interferometric angle errors. Such a simplisticfilter form cannot exactly represent the precision attitude memoryachievable when a more complete IMU and GPS integration is mechanized.This prevents the optimal merging of past interferometric measurementsand restricts the achievable measurement accuracy.

[0025] Ignagai integrates the Inertial Sensor System and interferometricrange system through a filter applied to a Euler angle. This approachresults in a mathematical problem as the system crosses the earth poles.A coordinate system switch is required as the platform reaches higherlatitudes. This is undesirable and reduces the generality of theinvention for general platform geodetic motion.

[0026] Two more patent examples include U.S. Pat. No. 5,672,872 toYeong-Wei and U.S. patent 5,809,457 to Yee. Both Yeong-Wei and Yeedescribe a generalized motion characterization system employing a GPSantenna and receiver integrated to an IMU device via a Kalman filter.Both Yeong-Wei and Yee inventions use a single GPS antenna rather thanthe dual antennas of the Buchler and Ignagai inventions. Yeong-Weispecifically describes the well-known problem of such single-GPS-antennamechanizations: persistent maneuvers are required to enable the headingattitude to be observable. Purposeful aircraft maneuvers are describedas necessary for the example aircraft embodiment. Yee is specialized toan application where the GPS antenna and IMU are located to theboresight of a sensor or antenna system. However, Yee makes no referenceto the problem of heading errors when persistent horizontal planemaneuvers are not present. Yee makes no mention of intentional maneuversfor achieving the heading alignment. Neither Yeong-Wei nor Yee mentionsthe use of dual GPS antennas for the purpose of avoiding the headingdrift when horizontal plane motion is not present.

SUMMARY OF THE INVENTION

[0027] Numerous commercial applications demand the pointing of a sensorboresight towards a location known in geodetic coordinates. Someemerging applications include pointing a highly directional antenna atan orbiting broadband satellite or pointing a sensor at a pre-determinedground location from an aircraft or ground vehicle and controlling thethrottle, braking, and suspension systems to insure safety andstabilization of automobiles. Many other applications exist that requirethe attitude of a platform structure to permit maneuvering in geodeticspace, such as the control of an aircraft in flight. Finally, manyapplications exist where the boresight of a sensor is required to beknown, but not controlled, for the purpose of geo-registering theinformation received by the sensor. This is the case, for example,during the collection of image sequences that are to be used forreconstruction of objects observed within the images or for mosaicking asequence of images onto a common map coordinate system.

[0028] The prior art provides approaches to the commercial requirements;however, each of the prior art approaches must be tailored to thespecific platforms, requires costly hardware components and/orinstallation techniques, imposes maneuver restrictions on the platforms,and does not take full advantage of the available GPS and IMUmeasurements.

[0029] The present invention provides a complete six-degree of freedomgeodetic characterization of an arbitrary dynamic or stationaryplatform. The geodetic characterization includes position, velocity,acceleration, attitude and attitude rates. The present invention posesno restriction on the motion of the platform and requires no electricalconnectivity to the platform except for power. Furthermore, systemsemploying the principles of the present invention can be bothmanufactured and installed at costs significantly less than systemsdefined in the prior art.

[0030] One embodiment of the present invention includes two navigationGPS antennas, three rate gyroscopes, three accelerometers, and at leastone processor to calculate the geodetic characterization of theplatform. The processor(s) determine an integrated navigation solutionthrough signals received by the navigation GPS antennas and throughsignals derived by the gyroscopes and accelerometers.

[0031] In the process of determining a navigation solution, thenavigation GPS antennas, preferably electrically similar, feed receivedRF signals to two RF downconverters. Both RF downconverters utilize thesame thermally controlled oscillator so that any oscillator-inducednoise is common-mode between the two RF front-end channels. Signalsoutput by the downconverters go into a single, commercially available,12-channel, correlator chip that tracks pseudorandom noise signals fromup to twelve GPS satellites and outputs channel tracking information,which is an input to the processor(s).

[0032] The processor(s) use the channel tracking information todetermine the time-of-transit for each GPS signal from its respectiveGPS satellite. Each time-of-transit has a common-mode bias due to theprocessor clock error. The processor(s) control the GPS satellite signaltracking process for each channel and decode the digital messages alsocontained in the GPS satellite signals. If four GPS satellites aretracked, then the processor(s) determine the common mode clock bias andthe geodetic position of the platform using methods well known in theart.

[0033] The processor(s) also accept data from the six IMU sensors: thethree rate gyroscopes mounted along orthogonal axes and the threeaccelerometers mounted collinearly with the gyroscope axes. The rotationrate and acceleration data provided by the gyroscopes andaccelerometers, respectively, are used by the processor(s) to form astrapdown navigation solution using methods that are well known in theart. The strapdown navigation solution results in a position, velocity,and attitude geodetic navigation solution. The processor(s) use awell-known transfer alignment procedure to determine the completethree-dimensional attitude of the platform by comparing the strapdownnavigation solution with the navigation solution derived solely from thenavigation GPS antennas, as described above. The processor(s) are ableto provide the geodetic characterization of the platform using rategyroscopes providing poorer than ten degrees/hour accuracy underarbitrary motion conditions. The principles of the present inventioninclude at least five innovations:

[0034] Utilization of available spare capacity within commerciallyavailable low cost GPS receivers enables GPS interferometry using only asingle GPS receiver. This provides both cost advantages and accuracyimprovement because the same oscillator is used for downconversion ofboth GPS antenna signals.

[0035] Close spacing of two GPS antennas, down to about 3 inches,depending on accuracy requirements of the application. This enablessimplified packaging, with less space involvement, and installation tothe mobile platforms. Close antenna spacing also minimizes the effectsof multipath interference on the attitude solution.

[0036] Tight integration of the single-GPS-antenna transfer alignmentprocess with the dual-antenna GPS interferometry process. This yieldsheading estimation independent of the GPS interferometry solution sothat heading ambiguities normally resulting from interferometricsolutions alone are immediately resolved. This obviates the requirementsfor heading initialization procedures such as gyrocompassing,alignment-to-velocity, or use of a magnetic compass from movingplatforms. For a stationary platform, integration with the IMU enables asimple method for resolving the heading ambiguities normally plaguingGPS-only attitude measurement methods.

[0037] Use of single-difference GPS carrier phase measurements. Thisensures that uncorrelated scalar measurements are provided to a Kalmanfilter as is required for optimal estimation. This enables improvedmeasurement accuracy over scalar double-difference measurements that arefundamentally correlated.

[0038] Acceleration aiding of the GPS receiver channels from the IMUinformation. This allows tightening the channel track loop bandwidths bypredicting platform velocity providing added multipath resistance overclose antenna spacing and the narrow correlator technologies well knownin the art.

BRIEF DESCRIPTION OF THE DRAWINGS

[0039]FIG. 1 is a pictorial diagram of an example broadbandcommunication scenario that is enabled by an motion characterizationsystem that is developed according to the principles of the presentinvention;

[0040]FIG. 2 is a high-level block diagram of the measurement andprocessing components of the motion characterization system of FIG. 1;

[0041]FIG. 3 is an electromechanical schematic diagram showing thecentral concept underlying GPS interferometry used by the motioncharacterization system of FIG. 1;

[0042]FIG. 4 is a block diagram of an example implementation of themotion characterization system of FIG. 2 having an Inertial MeasurementUnit (IMU) and a GPS receiver with an integrated Digital SignalProcessor (DSP);

[0043]FIG. 5 is a schematic diagram depicting a preferred embodiment ofthe motion characterization system in FIG. 4 and showing thesegmentation of navigation signals to support processing into navigationchannels and interferometry channels;

[0044]FIG. 6 is a vector diagram showing the measurement of three axesof acceleration and three axes of attitude rate by the IMU in FIG. 5after the calibration of the IMU to align the axes;

[0045]FIG. 7 is a schematic diagram of the IMU of FIG. 5 and shows theintegration of three accelerometers, three gyroscopes, and amicroconverter for analog-to-digital conversion and processing;

[0046]FIG. 8 is a flow diagram for the DSP-based GPS receiver of FIG. 5and shows the selection and allocation of navigation signal channels,the use of navigation and interferometry correlators, the aidedmeasurement of system parameters, and the use of a Kalman Filternavigator to provide a navigation solution, clock corrections, aidinginformation, and channel allocation information;

[0047]FIG. 9 is an antenna beam diagram showing the characteristics ofbroadband communication at high frequencies that pose fundamentalrequirements on attitude measurement accuracy;

[0048]FIG. 10 is a plot produced by a system simulation for the motioncharacterization system modeled in the block diagram of FIG. 5, whereattitude measurement error is parameterized by antenna baseline length;

[0049]FIG. 11 is another plot produced by the system simulation for themotion characterization system modeled in the block diagram of FIG. 5,where attitude measurement error is parameterized by gyroscope error;and

[0050]FIG. 12 is a block diagram that shows the integration of themotion characterization system into a broadband communication system.

[0051] The foregoing and other objects, features and advantages of theinvention will be apparent from the following more particulardescription of preferred embodiments of the invention, as illustrated inthe accompanying drawings in which like reference characters refer tothe same parts throughout the different views. The drawings are notnecessarily to scale, emphasis instead being placed upon illustratingthe principles of the invention.

DETAILED DESCRIPTION OF THE INVENTION

[0052] A description of preferred embodiments of the invention follows.

[0053] The current explosive growth in mobile vehicle display productsis accompanied by increased demand for robust access to high-qualityspatial information and to broadband data sources, such as streamingvideo, digital television, and high definition television (HDTV). Thepresent invention can be used to facilitate delivery of multimediabroadband data to users in vehicles, such as cars, planes, trains,boats, and airplanes. New generations of satellite-based broadbanddelivery systems use Low Earth Orbit (LEO) satellites operating at 20GHz or higher frequencies and require precise pointing of highlydirectional antennas to achieve high data rates.

[0054] The present invention permits use of poor performance, low-costmotion sensing devices both to enable accurate, affordable, antennapointing solutions for broadband mobile communications and to permit therobust delivery of spatial information to both military and commercialplatforms. These new delivery systems place stringent requirements onthe user equipment for antenna pointing accuracy, operation in adversemultipath environments, satellite tracking performance, andcommunication effectiveness to achieve continuous operation. Userequipment for fixed terminals can use traditional mechanical antennaapproaches. User equipment for mobile vehicles, however, demands moreinnovative solutions to meet requirements for unobtrusive surfacemounting, high pointing accuracy from a high-dynamics moving platform,and low satellite-to-satellite switching times.

[0055]FIG. 1 is a pictorial diagram of an example application that mayemploy the present invention. The example application is a mobilecommunications system that provides, for example, video content to amoving vehicle 3. The vehicle 3 is equipped with an antenna 1 that iscapable of steering a beam 2 at a broadband, content-delivery satellite4 providing the video content. The antenna 1 has an integrated geodeticmotion characterization system (shown in FIG. 2), employing theprinciples of the present invention, that uses navigation carriersignals from the Global Positioning System (GPS) satellites and motionsignals from motion sensing devices (shown in FIG. 2) to calculate roll,pitch, and yaw angles of the vehicle 3. The antenna 1 uses these angles,or beam angle control signals calculated therefrom, to keep the beam 2pointing at the content-delivery satellite 4. Keeping the beam 2pointing at the content-delivery satellite 4 results in good signalquality of the video signal displayed in a display 5 viewed bypassengers in the vehicle 3.

[0056] The present invention also provides characterizations of vehiclemotion that can be applied to improved vehicle safety systems,enhancements in occupant convenience, evolutionary development oftelematics and communications systems, and delivery of data to improvedvehicle displays. Further, the present invention provides an innovative,low-cost measurement solution that allows consolidation of discreteelements and the synergistic combination of hardware and softwaresystems.

[0057] Table 1 is a chart detailing vehicle systems for safety andbroadband access, with the associated components and sensors listed inthe decision support and principal sensors columns, respectively. Thecomments column includes a list of example applications and uses. TABLE1 Vehicle Decision Principal System Support Sensors Comments SafetyBrake Integrated Unintended change in modulation, gyroscopes, directionor orientation; steering accelerometers, excessive roll system, and GPSRoad condition monitoring suspension, Telematics support and engineVibration signature control Stabilized Road lane surveillance camera andCollision avoidance and pre- radar crash recognition Broadband AntennaIntegrated Satellite-based and tower- Access pointing gyroscopes, basedcommunications for accelerometers, high data rate information and GPS

[0058]FIG. 2 is a schematic diagram of an embodiment of the motioncharacterization system 6 employing the principles of the presentinvention that can be integrated into the antenna 1 of FIG. 1 orapplications listed in Table 1. The motion characterization system 6includes two antennas 7, motion sensing devices 8, and at least oneprocessor 9. The antennas 7 and motion sensing devices 8 are rigidlyconnected, directly or indirectly, to the body or platform, such as avehicle rooftop, whose angular attitude is being sensed.

[0059] The motion characterization system 6 uses the two antennas 7 toreceive navigation signals, the motion sensing devices 8 to provideinformation about body motion, and the processor 9 to estimate themotion of the body for delivery to other system applications. Thenavigation signals may be transmitted by GPS, GLONASS, Galileo, theGlobal Navigation Satellite System (GNSS), or other navigation systemsas available. The motion sensing devices 8 may include gyroscopes,accelerometers, magnetometers, tilt meters, speed measurement devices,navigation receivers, or other sensors. The processor 9 may be ageneral-purpose computer, digital signal processor (DSP), applicationspecific integrated circuit (ASIC), or other computing device. Thepreferred embodiment uses minimal number of motions sensing devices toachieve performance objectives, but can be extended to includeadditional motion sensing devices and other sensors to improveeffectiveness or extend the number of simultaneously supportedapplications.

[0060] The processor 9 uses the GPS signals and motion measurements toachieve sufficient motion estimation accuracy for the pointing, safety,telematics, and control applications. Navigation systems, such as GPS,provide precision positioning at all earth locations, at commoditypricing that is typically less than $50 for commercial applications. GPShowever, does not provide attitude information. Therefore, the motioncharacterization system 6 determines both the orientation and change oforientation of the receiving platform by other techniques. The motioncharacterization system 6 measures attitude, as parameterized by roll,pitch, and yaw, under all motion conditions, including the difficultsituation of no motion.

[0061] When the platform is nominally horizontal, to within +/−30 deg,and the platform is stationary or moving at walking-to-driving speeds,neither magnetic compass nor accelerometer-alone tilt sensors aresufficient for the approximately 0.5 deg geodetic attitude measurementaccuracy required for broadband mobile communication. Magnetic compasssolutions are sensitive to local magnetic disturbances, andaccelerometer-only solutions are sensitive to platform lateralaccelerations.

[0062] Although Earth-rate sensing through gyrocompassing, GPSinterferometry, and transfer alignment (TA) are possible implementationapproaches, the limitations associated with these approaches makes themunsuitable for an application such as content delivery to mobilecommunications systems. For example, the problems associated with TAstem from the inability to sense yaw attitude directly. TA requireschanges in vehicle velocity to enable estimation of yaw from velocitymatching and requires precision gyroscopes because of the algorithmicneed for heavy smoothing of the platform motion. The present inventionovercomes this dilemma by sensing the yaw attitude from a completelydifferent source—dual antenna interferometry. Thus, the motioncharacterization system 6 combines TA with dual antenna interferometryto achieve the approximate 0.5 degree geodetic attitude measurementaccuracy required for the broadband mobile communication system andother applications.

[0063]FIG. 3 is a high level schematic diagram of dual antennainterferometry as used by the motion characterization system 6, andconsists of GPS antennas 7, associated receiver channels 10, and a rangedifference calculation unit 11 encapsulating inertial measurement,signal processing, and estimation functions. The difference calculationunit 11 provides signal phase measurements that are accurate tomillimeter precision after GPS interferometry. The geodetic attitude iscalculated as sin(θ)=ΔR/L , where ΔR is the difference in GPS signalphase and L is the antenna baseline length.

[0064]FIG. 4 is an embodiment of the motion characterization system 6including the two antennas 7 and one or more substrates containing themotion sensing devices 8, processor(s) 9, and other interfacecomponents. In one embodiment, the processor(s) 9 include a DSP-basedGPS receiver 12 with excess capacity to support the GPS, navigation,interferometry, and control calculations. Additional processors may berequired for some complicated control applications and may be programmedto operate in a parallel manner. In one embodiment, the motion sensingdevices 9 include an Inertial Measurement Unit (IMU) 13 to provide themotion measurements of the platform or body.

[0065] The motion characterization system 6 provides acceptableperformance for high data rate broadband applications while permittinguse of poor quality Micro Electromechanical System (MEMS) devices in theIMU 13 and a commodity-priced DSP-based GPS receiver 12 for theprocessor 8. Better quality devices will lead to more accurate attitudemeasurement; however, with only poor quality MEMS devices (e.g., rategyroscopes having poorer than 10 degrees/hr accuracy), the motioncharacterization system 6 achieves the less than 1-degree attitudemeasurement accuracy required for high data rate, broadbandcommunications with LEO satellites at Ka band.

[0066] The motion characterization system 6 requires only two antennasbecause TA provides precision estimates of roll and pitch. In addition,a heading solution provided by the motion characterization system 6 isrelatively insensitive to GPS antenna spacing because of the smoothingbenefits of even low-accuracy inertial components. While considerableeffort has gone into optimizing techniques for GPS interferometry andTA, no commercially available systems rely on the integration of thetwo. The result is the motion characterization system 6 having anelegant implementation of a simple electronics architecture that can bepopulated with a handful of breakthrough technology chips and/orcomponents.

[0067] When the platform is stationary, the processing accuratelymeasures the roll and pitch attitude relative to the local vertical fromthe measurements provided by the motion sensing devices. The processor 9uses the differential carrier phase measurement from GPS interferometryto determine yaw; however, the yaw estimate from a single GPS satelliteis ambiguous due to the 0.19 m GPS wavelength. When the navigation andinterferometry GPS antennas track multiple GPS satellites, an algorithmresolves the interferometric ambiguity in yaw.

[0068] The GPS receiver 12 may be a modem GPS receiver that uses twelvecorrelator channels to search the complete range-Doppler space for GPSnavigation signals, reducing the time-to-first-fix (TTFF) and enablingrapid initialization of the position solution on startup or followingloss of GPS satellite lock. However, the number of visible GPSsatellites is very rarely over nine, and frequently only five to seven;thus, the GPS receiver 12 nearly always has access to spare correlatorchannels after initialization. In addition, performance improves onlymarginally when over six GPS satellites contribute to the solution.Thus, once several GPS satellites are acquired, four to five of thecorrelator channels are unused, and the motion characterization system 6uses the spare channels for interferometry. The traditionalinterferometric solutions have multiple parallel receivers that eachtrack the same GPS satellites. For example, the common implementation ofa conventional GPS receiver has twenty-four correlator channels so thatsix GPS satellites from those in view can be tracked on each of fourantennas.

[0069] GPS receivers are often mechanized with a single radio frequency(RF) front end and a 12-channel correlator. The RF front end convertsthe input GPS RF signal from an associated antenna to a digitalintermediate frequency (IF) signal that is then fed into each of theidentical twelve channels of the correlator chip for tracking up totwelve GPS satellites.

[0070]FIG. 5 is a preferred embodiment of the motion characterizationsystem 6 using navigation signal antennas 7, two low noise amplifiers(LNAs) 14 to establish correct signal levels, and two RF front ends 21,which are driven by a common oscillator 16 to reduce system noisefigure.

[0071] The motion characterization system 6 uses one of the two GPSantennas 7 as a navigation GPS antenna, feeding RF signals to a set ofnavigation channels 17, which permits the receiver 15 to use a GPSsatellite acquisition process that is identical to the conventional GPSreceiver. Typically, the correlator channels in the DSP-based GPSreceiver 15 use a fast acquisition process on as many available channelsas necessary to process signals from all GPS satellites in view. Themotion characterization system 6 produces a complete geodetic positionand velocity solution. When combined with the data from the IMU 13, thissolution also gives excellent roll and pitch attitude, and good headinginformation when the platform is persistently maneuvering in thehorizontal plane. Without such persistent maneuvers or when the platformis stationary, poor heading measurements result with only usingnavigation channels.

[0072] Following initialization, the motion characterization system 6uses the second of the GPS antennas 7 as an interferometry antenna,which feeds RF signals to the remaining GPS receiver channels, referredto as interferometry channels 18. Through interferometric rangemeasurement, the GPS satellites provide information on the vehicleheading relative to north for augmenting the heading informationprovided by the IMU 13 and navigation antenna alone. The IMU 13 andnavigation antenna provide sufficient information to allow excellentroll and pitch attitude information.

[0073] The preferred embodiment uses a single GPS receiver to achievereduced GPS phase measurement errors because the common oscillator 16 isused for both antenna paths. Also, platform heading is known to anaccuracy of 1-2 deg, independent of the two-antenna interferometricprocess, through the single-antenna-plus-IMU solution with an optionalmagnetic compass. The accurate heading combined with close GPS antennaspacing enables a unique interferometric solution for the heading asrefined through the interferometric process.

[0074] GPS interferometry that uses three or four antennas can achievethree-dimensional attitude measurement without inertial aiding, butrequires antenna spacing on the order of 1 meter to achieve sufficientaccuracy. A single GPS antenna and receiver when combined with anInertial Measurement Unit (IMU) that includes three rate gyroscopes andthree accelerometers can also achieve three-dimensional attitudemeasurement. However, this device requires lateral maneuvers of theplatform so that velocity matching between the GPS and inertialsensor-derived velocity solutions can occur. The present invention,however, uses two closely spaced GPS antennas combined with an IMU toprovide high accuracy for both stationary and moving vehicles.

[0075] Because the motion characterization system 6 uses two antennas 6that can be spaced as closely as three inches apart, typicalinstallation costs on the platforms are reduced. Also, though manyembodiments are possible, a single embodiment of the invention issuitable for all candidate air, space, ground, and sea platforms withminimum modification. The antennas used on a platform are preferablycompact and very closely spaced so that only a single compact,flush-mount component is mounted to the upper surface of the platform.Also, in one embodiment, no external equipment is required to be on theplatform for generating the measurement other than a power source.

[0076] Alternative embodiments may use a different oscillator for eachRF front end, a DSP-based GPS receiver for navigation functions and aseparate DSP-based GPS receiver for interferometry functions, a GPSreceiver and a separate DSP for processing functions, and otherarchitectural combinations. The preferred embodiment is simple, andleads to a low cost, high performance solution. The DSP-based GPSreceiver 12 also provides navigation and interferometry functions inaddition to typical GPS correlator and information delivery functions.

[0077] The IMU 13 of FIG. 5 develops estimates of acceleration andattitude rates along three axes. As shown in FIG. 6, the IMU 13 developsestimates along a first axis 19, a second axis 20, and a third axis 21.In practice, acceleration and attitude rates are measured alongdifferent, non-orthogonal triads of axes that are subsequentlyorthogonalized and aligned using a calibration procedure. Subsequentprocessing uses the parameters of the error model that result frominitial calibration. The error model includes bias, scale factor, noiseproperties, and various angular errors among the instrument axes,including: three non-orthogonalities for the accelerometer triad, threenon-orthogonalities for the gyroscope triad, three misalignments betweenthe accelerometer and gyroscope triads, and three misalignments to abody frame. The calibration software, optionally executed by a processor(not shown) in the IMU 13 or other processor 9 in the motioncharacterization system 6, includes a Kalman filter with the error termsas free parameters that are determined using Maximum LikelihoodParameter Estimation (MLPE) optimization or other suitable optimizationtechnique. After calibration, the IMU 13 in FIG. 5 provides calibratedacceleration and attitude rate data along three measurement axes.

[0078]FIG. 7 is a block diagram of an embodiment of the IMU 13. In oneembodiment, the IMU 13 uses three MEMS accelerometers 22 and three MEMSgyroscopes 23 for a low-cost solution. A microconverter 24 digitizesdata from the accelerometers 29 and the gyroscopes 30, accumulates setsof digitized data, and embeds synchronization data indicating a GPSepoch provided by the GPS receiver 12. The tight coupling of theinterferometry solution with the MEMS-based IMU improves the overallperformance of the motion characterization system 6.

[0079]FIG. 8 is a functional diagram of processes executed in theDSP-based GPS receiver 12 in FIG. 5. A channel allocator 25 orchestratesthe flow of data from the two RF front ends 15 (FIG. 5). Once inside theDSP, the data is allocated to navigation correlators 26 andinterferometry correlators 27 that are logically formed from a set ofcorrelators available within the GPS receiver 12. The process executingin the GPS receiver 12 configures the navigation channels to track thesmallest number of GPS satellites that provide an acceptable navigationsolution and configures the interferometry channels to track the GPSsatellites most nearly orthogonal to the antenna baseline and preferablylow on the horizon.

[0080] As shown in FIG. 8, the measurement processing 28 includes coderange and carrier phase processing 29 to support navigation functions.The measurement processing 28 also includes interferometric processing30 to support interferometry calculations. The measurement processing 28provides measurement models, linearized measurement models, errormodels, and measurement and error propagation information used bysubsequent processing.

[0081] A Kalman filter navigator 31 provides the estimation processingused to merge the IMU and GPS measurements. Kalman filtering, which iswell known in the art, requires a statistical mathematics model of theunderlying system dynamics and the measurement processes. The accuracyof the Kalman filter results is dependent both on the accuracy of theunderlying models and on the adherence of the models to the constraintsimposed by the Kalman filter formulation.

[0082] The measurement processing 28 and the Kalman filter navigator 31use fundamental observables to infer system behavior. The GPS receiver12 thus uses IMU measurements, selected GPS signal observables, and aspecifically formulated Kalman filter state model to estimate attitude.

[0083] All GPS receiver 12 uses pseudorandom noise (PRN) code sequencesto synchronize the correlator channels for each tracked GPS satellite.This correlation process provides a measure of the transit time of thesignals from each GPS satellite to the user. This transit timecomputation is relatively accurate for all GPS satellites being trackedbut contains an uncertainty due to the receiver oscillator forming thebasis of the clock. Use of four GPS satellites allows solution of thethree-dimensional location of the user and the user clock error. The lowrate digital message contains information about the calibration of theGPS satellite clocks, precise orbital data for each acquired GPSsatellite, and the almanac containing less precise orbital data for allGPS satellites.

[0084] The mechanization of the GPS position solution is of littleutility to the determination of attitude. Instead, the motioncharacterization system 6 uses two basic GPS observables for attitudemeasurement, which depend on the coherence of the transmitted GPS signalwaveform. The two basic GPS observables are:

[0085] Integrated Carrier Phase (ICP)—Because the GPS waveform iscoherent, the GPS receiver can lock to the phase of the GPS satellitewaveform and integrate phase changes to arrive at a precise measure ofthe change in received carrier phase over measured time intervals.Because the GPS satellite orbit is precisely known, the motioncharacterization system 6 can predict the contribution to phase changeresulting from Doppler. The residual phase change is a measure of theaverage velocity of the GPS receiver during the measurement interval, aGPS epoch.

[0086] Dual-antenna carrier phase difference—For two closely spacedantennas, the carrier phase can be measured and used to inferinformation about the range difference between the two antennas and theGPS satellite. The range difference is ambiguous by the signalwavelength.

[0087] The ICP for a single receiver and single GPS satellite containserrors due to the stability of the ionosphere and uncertainty in the GPSsatellite orbit. However, by differencing the per-epoch ICP between twoclosely spaced antennas, then the resulting double differenced carrierphase measurement is free of errors from the GPS satellite orbit orionosphere. This measurement has mm-level accuracy with even low costGPS receivers.

[0088] While multiple-antenna interferometry can provide informationabout the attitude of the GPS baseline from single-epochmultiple-satellite observations, the velocity information from GPSrequires a more inferential approach. The attitude error from an IMUsolution propagates into a velocity error in proportion to the vectorcross product with the vehicle acceleration. Thus, an estimate of theattitude results by comparing the GPS precision velocity measurementwith the IMU-derived velocity. The motion characterization system 6 usesboth attitude inference phenomena simultaneously to provide an optimalestimate of the attitude.

[0089] The Integrated Carrier Phase observable to the jth GPS satelliteat the i+i th epoch can be described mathematically as

ICP _(j)(t _(i+1))=R _(j)(t _(i+1))−R _(j)(t _(i))+δƒ  (1)

[0090] where δƒ is the error in the receiver oscillator over the epoch.The range is given by

R _(j)(t _(i+1))={square root}{square root over ((r _(s) ^(j) (t_(i+1))−r _(u)(t _(i+1))·(r _(s) ^(j) (t _(i+1))−r _(u)(t_(i+1))))}  (2)

[0091] where r_(s) ^(j) is the position vector to the jth GPS satelliteand r_(u) is the position vector to the receiver in a common coordinateframe. Also,

R _(j)(t _(i+1))={square root}{square root over ((r _(s) ^(j) (T _(i))−r_(u)(t _(i))+δr)·(r _(s) ^(j) (t _(i))−r _(u)(t _(i))+δr))}  (3)

[0092] where $\begin{matrix}{\underset{\_}{\delta \quad r} = {{\underset{\_}{r}\quad {\overset{\prime}{\quad Y}}_{s_{j}}\Delta \quad T} + {\int_{t_{i}}^{t_{i + 1}}{\underset{\_}{r}{\overset{\prime}{Y}}_{u}{t}}}}} & (4)\end{matrix}$

[0093] Linearizing with respect to δr yields $\begin{matrix}{{R_{j}\left( t_{i + 1} \right)} = {{R_{j}\left( t_{i} \right)} + {\frac{\left( {{\underset{\_}{r}}_{s_{j}} - {\underset{\_}{r}}_{u}} \right)}{R_{j}\left( t_{i} \right)} \cdot \underset{\_}{\delta \quad r}}}} & (5)\end{matrix}$

[0094] or $\begin{matrix}{{{R_{j}\left( t_{i + 1} \right)} = {{R_{j}\left( t_{i} \right)} + {{\underset{\_}{u}}_{j} \cdot \underset{\_}{\delta \quad r}}}},\quad {{\underset{\_}{u}}_{j} = \frac{\left( {{\underset{\_}{r}}_{s_{j}} - {\underset{\_}{r}}_{u}} \right)}{R_{j}\left( t_{i} \right)}}} & (6)\end{matrix}$

[0095] where u_(j) is the unit vector to the jth GPS satellite.Substituting yields

ICP _(j)(t _(i+1))=u _(j) ·δr+δƒ  (7)

[0096] Equation (7) is the measurement equation relating the observableICP to the IMU 13 and GPS clock errors over an epoch. The term δr fromequation (4) pertains to the integral of the velocity and not theinstantaneous velocity, which is important because the IMU errorequation propagates the continuous velocity error between epochs.

[0097] Most IMU/GPS integration solutions assume the availability of acontinuous GPS velocity measure, which is derived from afrequency-lock-loop within the hardware and sampling the resultinglocked frequency. Because of the large GPS satellite-induced Doppleroffset, an accurate measurement of high instantaneous velocity requiresan extremely precise measurement of the continuous instantaneousvelocity. High-end GPS achieves velocity estimation accuracy of0.03-m/sec. The motion characterization system 6 uses the integratedvelocity rather than the instantaneous velocity to allow an order ofmagnitude accuracy improvement in performance at an order of magnitudereduction in cost.

[0098] The prior art has not used this strategy for mechanizationreasons, which the Kalman filter navigator 31 of the present inventionovercomes. A Kalman filter state is added for each GPS satelliteaccording to δ_(r) Y _(j) =u _(j) ·δv  (8)

[0099] which ignores, temporarily, the coordinate frame of themeasurements. A measurement must also be added for each GPSsatellite-specific state according to

Δδr _(m) =δr(t _(i+1))−δr(t _(i)).  (9)

[0100] Thus, the measurement equation (9) is a function of thedifference between the current state and a past state. Such a Kalmanfilter form is highly non-standard and results in cumbersome matrixforms. The Kalman filter navigator 31 supports this special case.

[0101] The dual-antenna carrier phase difference observable is the dotproduct of the antenna baseline (r₂ ^(b)−r₁ ^(b)) with the LOS to thejth GPS satellite (û_(j)). Using the assumption of the GPS satellitelocated at infinity leads to the following expression for thedifferential carrier phase (δρ):

û _(j) ^(n) ·C _(b) ^(n)(r ₂ ^(b) −r ₁ ^(b))=δρ+ρ  (10)

[0102] The unknown phase state error p accounts for phase from the twoindependent receivers. Upon filter startup, ρ is an arbitrary valuebecause of the receiver phase differences.

[0103] Equation (10) is linearized with respect to IMU-axes-to-n-frame(geodetic) misalignments, as well as for misalignments of IMU axes withrespect to the antenna baseline. By considering small geodetic angleerrors (Δθ) and antenna alignment errors (Δφ^(b)) in C_(b) ^(n), thefollowing expression results: $\begin{matrix}{{{\delta \quad \rho_{j}} - {{\underset{\_}{\hat{u}}}_{j}^{n} \cdot {{\overset{\sim}{C}}_{b}^{n}\left( {{\underset{\_}{r}}_{2}^{b} - {\underset{\_}{r}}_{1}^{b}} \right)}}} = {{{\underset{\_}{\hat{u}}}_{j}^{n} \cdot \left\{ {\underset{\_}{\Delta \quad \theta} \times {{\overset{\sim}{C}}_{b}^{n}\left( {{\underset{\_}{r}}_{2}^{b} - {\underset{\_}{r}}_{1}^{b}} \right)}} \right\}} + {{\underset{\_}{\hat{u}}}_{j}^{n} \cdot \left\{ {{\overset{\sim}{C}}_{b}^{n}\Delta \quad {\underset{\_}{\varphi}}^{b} \times \left( {{\underset{\_}{r}}_{2}^{b} - {\underset{\_}{r}}_{1}^{b}} \right)} \right\}} + \rho}} & (11)\end{matrix}$

[0104] where {tilde over (C)}_(b) ^(n) represents the misaligeddirection cosine matrix from the strapdown navigation computationalprocess 32.

[0105] Equation (11) is the measurement equation for the Kalman filter.The left side of Equation (11) defines the measured-minus-predictedphase difference. The right side of Equation (11) represents the errorsin this estimate expressed in terms of (i) IMU and antenna baselinealignment errors and (ii) receiver-to-receiver phase errors. The antennaalignment enters the equation in a similar manner as the IMU alignmentexcept that the antenna alignment is assumed constant in a body axisframe. The antenna baseline alignment error states are typicallyinitialized with standard deviations of several degrees, which isreduced during processing as the geodetic angular errors are reducedthrough the traditional transfer alignment process. Only two of thesmall angular errors for the three angles in the vector Δφ^(b) are usedsince rotation about the antenna baseline is not observable. However,the formulation keeps the three elements in the solution to allow anarbitrary antenna baseline axes orientation relative to the IMU axes 26,27, 28.

[0106] Effective system integration requires use of the IMU-to-GPSbaseline misalignment as a component of the Kalman filter. The additionof the second GPS antenna forms a geometric baseline. The alignmentaccuracy of the baseline relative to the IMU is directly correlated tothe geodetic attitude estimation accuracy. The motion characterizationsystem 6 estimates the alignment during processing to avoid costly andnon-robust installation measurements.

[0107] The motion characterization system 6 may optionally use a novelSigmaEta strategy for implementing a Kalman filter from an arbitrarystate vector and measurement model. The motion characterization system 6may also use a tailored SigmaEta Kalman filter for the dual-antennaoperation, although other embodiments may use alternative forms for theKalman filter. The definition of the state vector elements depends onthe following construct:

{dot over (g)}b=η _(gb) −gb/τ _(gb)  (12)

[0108] Equation (12) represents a first-order Markov process with whitenoise input η and correlation time τ. The subscripts associate the inputand output noise and correlation with the specific state variable. Therepresentation of the statistical parameters allows the system error tovary in time in a statistically well-behaved manner. The clock model isa set of Brownian motion sequences, with the noise strengths derivedfrom evaluation of actual GPS receiver data.

[0109] Table 2 shows the elements of a state vector used in the Kalmanfilter navigator 31, where states 29-38 represent the interferometryphase. The error state standard deviations of these errors areinitialized at about 0.05 wavelengths. The ICP states are used to modelthe integral of the integral of velocity along the LOS to each GPSsatellite. The platform navigation state can be highly dynamic. TABLE 2State Name number Dynamical Representation Velocity error 1-3 δ{dot over(v)} ^(n) = δθ × C_(b) ^(n) a ^(b) + C_(b) ^(n) ab + C_(b) ^(n)[asfe]a^(b) Attitude error 4-6 δθ ^(Ý) = C_(b) ^(n)[(gb + [gsfe]ω _(b/i)^(b))x] Position error 7-9 δ{dot over (r)} ^(t) = C_(n) ^(t) v ^(n)Accelerometer 10-12 α{dot over (Y)}b = η _(ab) − ab/τ_(ab) biasGyroscope bias 13-15 {dot over (g)}b = η _(gb) − gb/τ_(ab) Accelerometer16-18 a{dot over (s)}fe = η _(asfe) − asfe/τ_(asfe) scale factor errorGyroscope scale 19-21 g{dot over (s)}fe = η _(gsfe) − gsfe/τ_(gsfe)factor error IMU-GPS latency 22 {dot over (T)}_(l) = η_(T) − T_(l)/τ_(T)GPS clock 23-25 {dot over (β)} = η_(β;) {dot over (f)} = β + η_(f); {dotover (c)} = f + η_(c) Baseline 26-28 {dot over (φ)} = 0 alignmentInterferometry 29-38 {dot over (Ω)} = η_(Ω) − Ω/τ_(Ω) phase ICP states39-48 Δ{dot over (r)}_(j) = C_(n) ^(t) u _(j) ^(n) · v ^(n)

[0110] The Kalman filter navigator 31 avoids the situation wheremeasurements are combinations of current and past state values by doinga reset on the ICP states at each epoch. The state values are set tozero, and the standard deviations are set to very near zero. The Kalmanfilter navigator 31 also sets the state correlation coefficients to zeroalong the rows and columns associated with the reset state. This processresults in a very simple implementation with the expense of addingauxiliary states and managing the reset process.

[0111] The measurement formulation for the dual-antenna Kalman filterincludes three sets of measurements corresponding to the coarse positionestimates, the code tracking process, the ICP measurements, and thedual-antenna measurements.

[0112] With two GPS receivers each tracking all GPS satellites in view,the Kalman filter used by the Kalman filter navigator 31 allows up to 30measurements per epoch, which correspond to ten measurements for eachmeasurement set. Each measurement is processed individually using theKalman filter update formulation.

[0113] The Kalman filter allows recursive processing of the measurementdata, which allows the sequential processing of measurements. However,for the processing to provide accurate results according to thepracticed art, each measurement must be uncorrelated with the priorsequential measurement. For interferometry, processing typicallydifferences integrated carrier phase measurements, first betweenantennas and then between GPS satellites to obtain a double differencemeasurement.

[0114] Carrier phase differencing between closely spaced antennas for acommon GPS satellite removes common-mode errors associated with theionosphere path length and GPS satellite transmission. However, acommon-mode receiver clock error remains following the differencing.Often, in the practiced art, the processing performs a second differencebetween signals from two GPS satellites to remove the common time biasin the common mode clock error. The sequential measurements now becomecorrelated if they include noise associated with a common GPS satellite.For example, if z_(A)=M_(B)−M_(A) and z_(B)=M_(C)−M_(A) representmeasurement differences between satellite B and satellite A andsatellite C and satellite A, respectively, then the measurements z_(A)and z_(B) are correlated because each measurement difference containsthe same noise from M_(A). Consequently, the correlations in theresulting double differenced measurements cannot be processed directlyby a straightforward Kalman filter formulation. The single-differencedmeasurements do not contain correlations; however, the Kalman filterstate vector dynamic modeling procedure must model the common-mode clockerrors. The Kalman filter navigator 31 uses the single-differencecarrier phase measurement model with CPU clock error model, and thedouble differenced carrier phase measurement may be used in alternativeembodiments.

[0115] Multipath interference in a GPS receiver results from receivingthe combination of the direct path and reflected path from a single GPSsatellite. The extraneous reflections occur from fixed structures in thesurroundings, such as buildings and towers, from terrain features withinthe surrounding environment, or from the portion of the platformstructure. In an urban environment in the proximity of tall buildings,multipath will result in pseudorange errors of 5-10 meters for affectedGPS satellites. In such situations, phase multipath can produceinterferometric solutions that are significantly in error. The motioncharacterization system 6 uses strategies for multipath mitigation thatinclude detecting and discarding GPS satellites with evidence ofmultipath, using closely spaced antennas, and having a carrier trackingloop that uses platform acceleration aiding. The strategies formultipath mitigation include:

[0116] Deep signal fades can occur with the phased addition of allsignal returns, resulting in loss of lock. Anomalous tracking conditionscan occur before the loss of lock and during re-acquisition. Because ofthe ability to selectively depend on the IMU navigation solution, themotion characterization system 6 can operate with fewer, possibly zero,GPS satellites for an extended period. Additionally, the motioncharacterization system 6 is capable of quickly discarding navigationdata from GPS satellites that are providing motion estimates notconsistent with measured accelerations or other GPS satellitemeasurements.

[0117] GPS antenna design, the design of antenna ground planes, and carein placing the GPS antenna on a platform offer some multipathprotection; however, multipath signals are often present in any complexurban scene or vehicle mounting surface. For path lengths that differconsiderably, as in the case for reflections from nearby buildings, GPSsignal tracking methods involving narrow correlator bandpass methods canprovide multipath protection on each receiver channel. However, becauseinterferometry relies on mm-level position differences, multipathreflections with even small path length differences appear differentlyat the two GPS antennas and can pose serious problems. As the twoantennas are brought closer together in the presence of a complexmultipath environment, both antennas are more likely to see the samereflected energy pattern. Therefore, the close spacing of the navigationantennas 7 used by the motion characterization system 6 mitigatesmultipath.

[0118] The individual channels of the correlator chips 26 and 27 provideboth pseudorandom noise (PRN) code tracking and carrier tracking foreach GPS satellite. Typically, the expected dynamics of the vehiclealong the line-of-sight (LOS) to the GPS satellite is the single mostsignificant aspect of the tracking loop designs. By aiding the trackingloops with acceleration along the LOS, the motion characterizationsystem 6 can anticipate the platform dynamics, thus enabling fasteracquisition, less sensitivity to spurious emissions, and greaterrobustness to multipath and vehicle dynamics. The motioncharacterization system 6 optionally determines acceleration aidingestimates using range-rate prediction to each carrier track loop alongwith adjustments to code and carrier track loop bandwidths and PRN codedither values. Acceleration aiding requires both measurement of thevehicle acceleration vector as well as knowledge of the geodeticorientation of the vehicle. The motion characterization system 6 may useparameterized tracking loops configured to mediate multipath.

[0119] The measurement processing 28 in the GPS satellite selectioncontrol compares the GPS signals for GPS satellites tracked at bothantennas. For non-multipath conditions, carrier/code loop processing foreach channel should be identical. For identical antennas andantenna-to-receiver signal paths, the only source of difference comesfrom on-platform multipath. Fortunately, redundant GPS satellites arelikely to exist for both navigation and interferometry purposes. A landnavigation system can perform well with only three GPS satellites inview and the integration with the IMU allows the three GPS satellites tobe used sequentially rather than simultaneously.

[0120] Broadband satellite data links use Ka band frequencies to achieveGHz-wide data bandwidth. At these higher frequencies, radio frequency(RF) energy is more highly focused for a given antenna size, and antennagain can be made very high along a preferred direction. The highdirectionality of Ka band transmission provides a natural immunity tointerference and signal leakage and the high-gain antennas can bemanufactured in compact sizes. However, Ka band communication suffersfrom higher atmospheric attenuation, and the narrow beamwidth 33 in FIG.9 of the communicating antennas demands more attention to pointing thebeam at the communication source.

[0121] Selecting an approach to pointing a receiving antenna at abroadband satellite source depends on the dynamics of the relativegeometry. Considering the satellite source, the pointing solutiondepends on whether the antenna is pointed at an earth-fixed source, asin the case of a Geosynchronous Earth Orbit (GEO) Satellite, or at asource moving relative to the earth, as in the case of a Low Earth Orbit(LEO) satellite. Considering the receiver antenna, the pointing solutionalso depends on whether the antenna is mounted on a rigid platform, suchas the top of a building, or on a dynamically moving platform, such asthe top of an automobile or an aircraft. There are also intermediatecircumstances where the platform may be slightly moving, such as on atower, or occasionally transported, as in an emergency situation.

[0122] For even the least stressful pointing scenario, a building topwith GEO satellite, the very narrow antenna beam must be preciselypointed. Manual setup requires both precision mechanical alignment andrealignment in the event the equipment is jarred, buffeted by winds, ormoved by vibrations. By achieving in a low cost solution the errorbudget specified for the most stressful pointing applications, which isthe moving vehicle with a LEO satellite network, the present inventionpermits a low cost solution having application to all broadband pointingsituations.

[0123] For communication from a moving vehicle as in FIG. 1, thepointing system deflects the antenna with respect to the vehicle tomaintain the proper pointing direction to the content-deliverysatellite. Deflecting the beam can be accomplished using electricaltechniques, mechanical techniques, or a combination of electrical andmechanical techniques. For an antenna having a fixed size as shown inFIG. 9, the present invention provides a pointing technique that keepsthe antenna mainbeam 33 pointed at a content-delivery satellite.

[0124] A detailed simulation of the invention models the GPS satelliteconstellation, vehicle motion, INS hardware, GPS receiver, and theprocessing performed by the motion characterization system 6 todemonstrate the value of augmenting transfer alignment with GPSinterferometry. Table 3 includes simulation parameters and correspondingnominal values. Results from the simulations, which are not shown, usingthe simulation parameters of Table 3 illustrate the operation oftransfer alignment without interferometry on a slow-moving groundvehicle, showing the sensitivity to vehicle motion and the reliance onhigh-quality gyroscope measurements. By adding one GPS antenna tosupport interferometric measurements, the results of the simulation showthe elimination of the drawbacks of transfer alignment. TABLE 3Simulation Parameter Nominal Value antenna baseline distance 12 inbaseline alignment sigma 1 mrad interferometric phase bias sigma 2 mminterferometric phase sigma 1 mm gyroscope bias sigma 500 deg/hrgyroscope scale factor error sigma 20000 PPM gyroscope noise 2.56deg/root-hr accelerometer bias sigma 10 mG accelerometer scale factorerror 20000 PPM sigma 0.4 m/s/root- hr accelerometer noise 200 secgyroscope error correlation time 200 sec acceleration error correlationtime 10 mm delta pseudorange error sigma 0.1 m pseudorange error sigma 8m GPS clock bias sigma 0.1 m/sec GPS clock oscillator bias sigma 10 mIMU lever arm to master GPS 0 m Speed 5 mph

[0125] All the problems associated with transfer alignment stem from theinability to sense yaw attitude directly. Transfer alignment requireschanges in vehicle velocity to enable estimation of yaw from velocitymatching and requires precision gyroscopes because of the algorithmicneed for heavy smoothing of the platform motion. The motioncharacterization system 6 overcomes this dilemma by sensing the yawattitude from a completely different source—dual-antenna interferometry.As discussed above the approach for sensing yaw attitude requires onlytwo antennas because transfer alignment provides precision estimates ofroll and pitch. In addition, the solution for sensing yaw attitudeprovided by the present invention is relatively insensitive to GPSantenna spacing because of the smoothing benefits of even low-accuracyinertial components. The tight coupling of the interferometry solutionwith the IMU makes sensing yaw attitude in a low cost solution possible.

[0126] The vehicle trajectory used for the simulation has a changingvehicle velocity profile that transfer alignment requires for goodperformance. By using a changing velocity profile, the simulationprovides a comparatively conservative view of the benefit of theinvention. The simulation uses values for the nominal IMU parametersthat are representative of automotive-grade MEMS accelerometers andgyroscopes. The MEMS gyroscope is 500-times poorer in bias and over 100times poorer in noise figure than the typical tactical gyroscope. TheMEMS accelerometer is only slightly poorer than the current tacticalaccelerometer. The GPS measurement quality is typical of commercialquality, low-cost units, and the error characteristics for the GPSinterferometry configuration reflects practical installationconstraints. The simulation uses a 1 mph nominal platform velocity toillustrate the performance of the motion characterization system 6 withonly slight platform motion.

[0127] The simulation results shown in FIG. 10 indicate that smallinterferometry baselines provide good yaw estimation accuracy. Forexample, a 12-in GPS antenna separation together with a nominal 1-mmphase error provides a yaw estimation accuracy of 1.7-mrad (0.1-deg).The 1-mm phase error over a 12-in antenna separation results in asingle-look angular accuracy of 3-mrad. The use of multiple GPSsatellites and the smoothing effects of the gyroscope measurementsfurther improve accuracy.

[0128] The simulation results shown in FIG. 11 indicate that accurateestimates of yaw are relatively insensitive to gyroscope accuracy overthe modeled region. In addition, although not shown, the roll and pitchestimation accuracy remains excellent. The interferometry is thedominant factor in yaw angle observability and not the smoothing thatresults from rate measurement. Additional simulation results are shownand described in U.S. Provisional Application No. 60/272,170, filed onFeb. 28, 2001; the entire teachings of which are incorporated herein byreference.

[0129] Traditional GPS-alone interferometry solutions require aninitialization step using sophisticated search procedures to overcomethe three-dimensional wavelength ambiguity associated with thedifferential range measurement. Transfer alignment provides an initialyaw estimate with vehicle motion; otherwise, an eight-position search ofthe 0-360 deg yaw space will be required. The dual-antenna solutionemployed by the motion characterization system 6 mitigatesinitialization by requiring ambiguity resolution over only a single axisof yaw. The excellent pitch and roll estimate provided by theaccelerometers provides improved performance over a conventionalGPS-alone interferometry system. In addition, in one embodiment, a short12-in baseline of the antennas 7 significantly reduces sensitivity toyaw uncertainty because the ambiguity is on the same order as thebaseline length. Thus, only a very coarse estimate of yaw, about 45 deg,ensures an unambiguous attitude solution.

[0130]FIG. 12 is a diagram of an example of a broadband communicationsystem 50 with integrated pointing control according to the principlesof the present invention. An example shown in FIG. 12 of the broadbandcommunication system 50 integrates an broadband antenna system 47, acommunications receiver and transmitter 34, a pointing controller 43,The broadband antenna system 47 consists of communications antenna array49 and one embodiment of the motion measurement system 6 mounted on oneor more substrates, which includes 2 GPS antennas, an InertialMeasurement Unit, an interferometric GPS receiver, and a processor.

[0131] The communications receiver and transmitter 34 may be constructedfrom a commodity chipset, applications specific chipsets, or discretecomponents. The broadband communications system 50 may include thecommunications functions typically found in a commercially availablecommunications receiver and transmitter. For the receive chain, thefunctions include downconversion and gain control 35, analog-to-digitalconversion 36, tuning and filtering 37, and demodulation and decoding38. For the transmit chain, the functions include encoding andmodulation 39, synthesis and filtering 40, digital-to-analog conversion41, and upconversion 42.

[0132] The pointing controller 43 uses the capabilities of the presentinvention as described above and adds the processing necessary toeffectively point the communications antenna array 49 at a transmittingsource or receiving sink. The pointing controller 43 includes RFprocessing 44, GPS processing 45, and filtering and data processing 46.Many other integration methods of the example broadband communicationsystem 50 are possible, as determined by cost and application.

[0133] While this invention has been particularly shown and describedwith references to preferred embodiments thereof, it will be understoodby those skilled in the art that various changes in form and details maybe made therein without departing from the scope of the inventionencompassed by the appended claims.

What is claimed is:
 1. An motion characterization system, comprising:two antennas, mounted to a rigid body, to receive navigation signals; acollection of motion sensing devices, including rate gyroscopesproviding poorer than ten degrees per hour accuracy, mounted on therigid body to provide electrical signals providing motion information;and a processor electrically coupled to process electrical signals fromthe antennas and the motion sensing devices to provide an attitudemeasurement of the rigid body under arbitrary motion conditions.
 2. Themeasurement system as claimed in claim 1, wherein the antennas areseparated by less than three wavelengths of a signal received from anexternal signaling source.
 3. The measurement system as claimed in claim2, wherein the external signaling source is a plurality of GPSsatellites.
 4. The measurement system as claimed in claim 3, wherein theantennas are separated by about 150 millimeters (mm).
 5. The measurementsystem as claimed in claim 1, wherein the motion sensing devices includeat least one MEMS device.
 6. The measurement system as claimed in claim5, wherein the processor processing the motion sensing devices providesan acceleration signal.
 7. The measurement system as claimed in claim 1,wherein the arbitrary motion conditions include general moving motions,constant velocity motions, and stationary motions.
 8. The measurementsystem as claimed in claim 1, wherein the attitude measurement isaccurate to within about 1 degree.
 9. The measurement system as claimedin claim 1, wherein one antenna is used supports navigation processingand the other antenna supports interferometry processing.
 10. Themeasurement system as claimed in claim 1, wherein alignment errorbetween the antenna baseline and the motion sensing devices is estimatedby software.
 11. The measurement system as claimed in claim 1, whereinthe processor includes a twelve-channel GPS receiver.
 12. Themeasurement system as claimed in claim 11, wherein after aninitialization process, unused channels in the GPS receiver (i) receivedata by one of the antennas supporting interferometry, and (ii) trackGPS satellites most nearly orthogonal to the antenna baseline.
 13. Amethod for determining attitude of a rigid body, comprising: receivingnavigation signals at the rigid body; measuring motion of the rigidbody, including rate with poorer than ten degrees per hour accuracy, andproviding corresponding motion signals; and processing the navigationsignals and motion signals to provide an attitude measurement of therigid body under arbitrary motion conditions.
 14. The method as claimedin claim 13, wherein the navigation signals are GPS signals.
 15. Themethod as claimed in claim 13, wherein the arbitrary motion conditionsinclude general moving motions, constant velocity motions, andstationary motions.
 16. An motion characterization system, comprising:platform means; means for receiving navigation signals at said platformmeans; means for sensing motion of said platform means and for providingassociated motion signals, including rate of said platform means with anaccuracy of poorer than ten degrees per hour; and means for processingthe navigation signals and the motion signals to provide an attitudemeasurement of said platform means under arbitrary motion conditions.17. A mobile system, comprising: a platform; a motion characterizationsystem including: (i) a first navigation antenna and second navigationantenna coupled to the platform to receive navigation carrier signals,(ii) a plurality of motion sensing devices coupled to the platform toprovide motion signals representative of motion of the platform, and(iii) a processor (a) coupled to the antennas to make range and carrierphase measurements of the navigation carrier signals at a plurality ofepochs defining the navigation carrier signals and to segment the rangeand carrier phase measurements for the navigation carrier signals into anavigation set and an interferometry set, the sets having at least onenavigation carrier signal for a plurality of navigation epochs andsupporting interferometry calculations and (b) coupled to the motionsensing devices to receive the motion signals and to convert the motionsignals into measurements of platform motion for a plurality of epochsdefined for the motion signals, the processor determining a navigationsolution including position and attitude of the platform from the rangeand carrier phase measurements for the navigation carrier signals andfrom measurements of platform motion developed from the motion signals;and a subsystem in communication with the motion characterization systemresponsive to the navigation solution.
 18. The mobile system as claimedin claim 17, wherein the motion sensing devices include rate gyroscopesproviding poorer than ten degrees per hour accuracy.
 19. The mobilesystem as claimed in claim 17, wherein the first and second navigationantennas are separated by less than three wavelengths of the navigationcarrier signal.
 20. The mobile system as claimed in claim 17, whereinthe navigation carrier signals are provided by a plurality of GPSsatellites.
 21. The mobile system as claimed in claim 17, wherein themotion sensing devices include at least one MEMS device.
 22. The mobilesystem as claimed in claim 17, wherein the platform motion includesgeneral moving motions, constant velocity motions, and stationarymotions.
 23. The mobile system as claimed in claim 17, wherein theattitude measurements are accurate to within about 1 degree.
 24. Themobile system as claimed in claim 17, wherein the first navigationantenna supports navigation processing and the other antenna supportsinterferometry processing.
 25. The mobile system as claimed in claim 17,wherein software executed by the processor corrects for alignment errorbetween a baseline defined by the first and second navigation antennasand a coordinate system defined by the motion sensing devices.
 26. Themobile system as claimed in claim 17, wherein the processor includes atwelve-channel GPS receiver.
 27. The mobile system as claimed in claim26, wherein, after an initialization process, unused channels in the GPSreceiver (i) receive data from the second navigation antenna, acting asan interferometry antenna, and (ii) track GPS satellites most nearlyorthogonal to a baseline defined by the first and second navigationantennas.
 28. The mobile system as claimed in claim 17, wherein theprocessor allocates, in an optimized manner, a plurality of navigationsignals to the navigation set or the interferometry set using navigationand interferometry performance estimates.
 29. The mobile system asclaimed in claim 17, wherein the processor improves the accuracy of therange, carrier phase, and interferometry processing for the navigationcarrier signals by providing estimates of acceleration along aline-of-sight from the platform to each of a plurality of navigationsignal sources.
 30. The mobile system as claimed in claim 17, whereinthe processor synchronizes the measurements of platform motion, providedby the motion sensing devices, using time estimates developed from thenavigation carrier signals.
 31. The mobile system as claimed in claim17, wherein the subsystem includes a directive antenna directing anassociated antenna beam via mechanical means.
 32. The mobile system asclaimed in claim 17, wherein the subsystem includes a directive antennadirecting an associated antenna beam via electronic means.
 33. Themobile system as claimed in claim 17, wherein the subsystem includes adirective antenna mechanically coupled to the platform and electricallycoupled to the motion characterization system to direct an associatedantenna beam in response to the navigation solution.
 34. The mobilesystem as claimed in claim 17, wherein the subsystem includes a vehiclesafety system.
 35. A method for determining attitude of a stationary ormoving platform, comprising: receiving navigation carrier signals;making range and carrier phase measurements of the navigation carriersignals at a plurality of navigation system epochs defining thenavigation carrier signals; segmenting the range and carrier phasemeasurements for the navigation carrier signals into a navigation setand an interferometry set, the sets (i) having at least one navigationcarrier signal for a plurality of the navigation system epochs and (ii)supporting interferometry calculations; receiving motion signalsrepresenting motion of the platform; converting the motion signals intomeasurements of platform motion for a plurality of epochs defined forthe motion signals; and determining a navigation solution includingposition and attitude of the platform from the range and carrier phasemeasurements for the navigation carrier signals and from themeasurements of platform motion developed from the motion signals. 36.The method according to claim 35, further including allocating, in anoptimizing manner, a plurality of navigation carrier signals to thenavigation set or the interferometry set using navigation andinterferometry performance estimates.
 37. The method according to claim35, further including improving the accuracy of the range, carrierphase, and interferometry processing for the navigation carrier signalsby providing estimates of the acceleration along the line-of-sight fromthe platform to each of a plurality of navigation system signal sources.38. The method according to claim 35, further including synchronizingthe measurements of vehicle motion, provided by the motion sensingdevices, using the time estimates developed from the navigation carriersignals.
 39. The method according to claim 35, wherein the navigationcarrier signals are received by two navigation system antennas that aremounted to the platform and the motion signals are provided by motionsensing devices also mounted to the platform.
 40. The method accordingto claim 35, wherein the navigation set is associated with one of thetwo navigation system antennas and the interferometry set is associatedwith the other of the two navigation system antennas.
 41. The methodaccording to claim 35, to further include providing the navigationsolution for use by a subsystem associated with the platform.
 42. Themethod according to claim 35, wherein the subsystem is a safety system,stability control system, pointing system, geodetic position controlsystem, attitude control system, or mapping projection system.
 43. Themethod according to claim 35, wherein the navigation carrier signals areprovided by a plurality of GPS satellites.
 44. An apparatus fordetermining attitude of a platform under arbitrary motion conditions,comprising: means for receiving navigation carrier signals; means formaking range and carrier phase measurements of the navigation carriersignals at a plurality of epochs defining the navigation carriersignals; means for segmenting the range and carrier phase measurementsfor the navigation carrier signals into a navigation set and aninterferometry set, the sets (i) having at least one navigation carriersignal for a plurality of navigation system epochs and (ii) supportinginterferometry calculations; means for converting the motion signalsinto measurement of platform motion for a plurality of navigation systemepochs defined for the motion signals; and means for determining anavigation solution including position and attitude of the platform fromthe range and carrier phase measurements of platform motion developedfrom the motion signals.